MfNeuPAN: 多フレーム点制約による動的環境での先読み型エンドツーエンドナビゲーション
MfNeuPAN: Proactive End-to-End Navigation in Dynamic Environments via Direct Multi-Frame Point Constraints
移動障害物の将来経路を予測するモジュールを組み込み、現在と未来の多フレーム点制約を用いて動的環境で先回りして障害物を回避するエンドツーエンドナビゲーション手法を提案した。
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著者: Yiwen Ying, Hanjing Ye, Senzi Luo, Luyao Liu, Yu Zhan, Li He, Hong Zhang
分類: cs.RO
原文アブストラクト
Obstacle avoidance in complex and dynamic environments is a critical challenge for real-time robot navigation. Model-based and learning-based methods often fail in highly dynamic scenarios because traditional methods assume a static environment and cannot adapt to real-time changes, while learning-based methods rely on single-frame observations for motion constraint estimation, limiting their adaptability. To overcome these limitations, this paper proposes a novel framework that leverages multi-frame point constraints, including current and future frames predicted by a dedicated module, to enable proactive end-to-end navigation. By incorporating a prediction module that forecasts the future path of moving obstacles based on multi-frame observations, our method allows the robot to proactively anticipate and avoid potential dangers. This proactive planning capability significantly enhances navigation robustness and efficiency in unknown dynamic environments. Simulations and real-world experiments validate the effectiveness of our approach.
